'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase					=logging.get_logger(__name__)

__UpperCAmelCase					={
    "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
    "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/config.json"
    # See all FNet models at https://huggingface.co/models?filter=fnet
}




class        a__ (  UpperCAmelCase__					):
     lowerCamelCase    :	List[Any]				="fnet"






     def __init__(					self						:						List[str]    ,							a						:						Tuple=3_20_00    ,							a						:						Optional[int]=7_68    ,							a						:						Optional[int]=12    ,							a						:						Optional[Any]=30_72    ,							a						:						Dict="gelu_new"    ,							a						:						Tuple=0.1    ,							a						:						Tuple=5_12    ,							a						:						str=4    ,							a						:						Tuple=0.02    ,							a						:						Union[str, Any]=1e-1_2    ,							a						:						Optional[int]=False    ,							a						:						List[str]=5_12    ,							a						:						Any=3    ,							a						:						Optional[Any]=1    ,							a						:						int=2    ,							**a						:						Optional[Any]    ,							):





         """simple docstring"""



         super().__init__(pad_token_id=a    ,							bos_token_id=a    ,							eos_token_id=a    ,							**a       )

         __lowerCamelCase            =    vocab_size
         __lowerCamelCase            =    max_position_embeddings
         __lowerCamelCase            =    hidden_size
         __lowerCamelCase            =    num_hidden_layers
         __lowerCamelCase            =    intermediate_size
         __lowerCamelCase            =    hidden_act
         __lowerCamelCase            =    hidden_dropout_prob
         __lowerCamelCase            =    initializer_range
         __lowerCamelCase            =    type_vocab_size
         __lowerCamelCase            =    layer_norm_eps
         __lowerCamelCase            =    use_tpu_fourier_optimizations
         __lowerCamelCase            =    tpu_short_seq_length

'''simple docstring'''




# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__UpperCAmelCase					={
    "configuration_efficientnet": [
        "EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientNetConfig",
        "EfficientNetOnnxConfig",
    ]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __UpperCAmelCase					=["EfficientNetImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __UpperCAmelCase					=[
      "EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST",
      "EfficientNetForImageClassification",
      "EfficientNetModel",
      "EfficientNetPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_efficientnet import (
      EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
      EfficientNetConfig,
      EfficientNetOnnxConfig,
  )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_efficientnet import EfficientNetImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_efficientnet import (
        EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        EfficientNetForImageClassification,
        EfficientNetModel,
        EfficientNetPreTrainedModel,
    )

else:
  import sys

  __UpperCAmelCase					=_LazyModule(__name__, globals()["__file__"], _import_structure)
